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<h1 id="作业描述文件">作业描述文件 </h1>
<pre class="language-text">用于描述一个完整的作业流程
</pre>
<hr>
<p>⚠ 文件名 <strong>必须</strong> 以 <code>rgr_</code> 或者 <code>clf_</code> 开头，代表任务类型分别为 <code>回归</code> 和 <code>分类</code></p>
<p>=&gt; 参考 <a href="https://docs.ansible.com/ansible/latest/reference_appendices/YAMLSyntax.html">YMAL语法</a></p>
<h3 id="作业描述配置">作业描述配置 </h3>
<pre data-role="codeBlock" data-info="yaml" class="language-yaml yaml"><code><span class="token key atrule">preprocess</span><span class="token punctuation">:</span>         <span class="token comment"># 预处理，可选项为 modules/preprocess.py 文件内节的各函数名</span>
  <span class="token key atrule">filter_T</span><span class="token punctuation">:</span>
    <span class="token punctuation">-</span> string
  <span class="token key atrule">project</span><span class="token punctuation">:</span> string   <span class="token comment"># 必须在 ['to_hourly', 'to_daily'] 里二选一</span>
  <span class="token key atrule">filter_V</span><span class="token punctuation">:</span>
    <span class="token punctuation">-</span> string

<span class="token key atrule">dataset</span><span class="token punctuation">:</span>            <span class="token comment"># 数据制作</span>
  <span class="token key atrule">exclusive</span><span class="token punctuation">:</span> bool   <span class="token comment"># 多特征变量建模是否除外自身 (default: False, ie. auto-gressive)</span>
  <span class="token key atrule">inlen</span><span class="token punctuation">:</span> int        <span class="token comment"># 条件序列窗长，知 in 推 out (default: 3)</span>
  <span class="token key atrule">outlen</span><span class="token punctuation">:</span> int       <span class="token comment"># 预测序列窗长，知 in 推 out (default: 1)</span>
  <span class="token key atrule">overlap</span><span class="token punctuation">:</span> int      <span class="token comment"># in/out 窗重叠长度 (default: 0)</span>
  <span class="token key atrule">split</span><span class="token punctuation">:</span> float      <span class="token comment"># 数据集划分，测试集占比 (default: 0.2)</span>
  <span class="token key atrule">encoder</span><span class="token punctuation">:</span>          <span class="token comment"># 分类任务的目标编码 (default: None)</span>
    <span class="token key atrule">name</span><span class="token punctuation">:</span> string    <span class="token comment"># 编码函数，可选项为 modules/dataset.py 文件内各函数名</span>
    <span class="token key atrule">params</span><span class="token punctuation">:</span>         <span class="token comment"># 编码函数的额外参数列表</span>
      <span class="token punctuation">[</span><span class="token key atrule">key</span><span class="token punctuation">:</span> value<span class="token punctuation">]</span>
  <span class="token key atrule">freq_min</span><span class="token punctuation">:</span> float   <span class="token comment"># 分类任务的非0类占比阈值，小于此阈值将忽略建模 (default: 0.0)</span>

<span class="token key atrule">transform</span><span class="token punctuation">:</span>          <span class="token comment"># 数值变换，可选项为 modules/transform.py 文件内各函数名</span>
  <span class="token punctuation">-</span> string

<span class="token key atrule">model</span><span class="token punctuation">:</span>
  <span class="token key atrule">name</span><span class="token punctuation">:</span> string      <span class="token comment"># 模型模板，可选项为 modules/models 目录下各文件名</span>
  <span class="token key atrule">params</span><span class="token punctuation">:</span>           <span class="token comment"># 依模型模板不同设置项也不同，详见各模板</span>
    <span class="token punctuation">[</span><span class="token key atrule">key</span><span class="token punctuation">:</span> value<span class="token punctuation">]</span>

<span class="token key atrule">seed</span><span class="token punctuation">:</span> int           <span class="token comment"># 全局随机数种子, (default: -1, ie. randomized)</span>
</code></pre><h3 id="数据制作流程">数据制作流程 </h3>
<h5 id="preprocess-数值预处理">preprocess 数值预处理 </h5>
<pre data-role="codeBlock" data-info="yaml" class="language-yaml yaml"><code><span class="token key atrule">preprocess</span><span class="token punctuation">:</span>         <span class="token comment"># 预处理，可选项为 modules/preprocess.py 文件内节的各函数名</span>
  <span class="token key atrule">filter_T</span><span class="token punctuation">:</span>
    <span class="token punctuation">-</span> string
  <span class="token key atrule">project</span><span class="token punctuation">:</span> string   <span class="token comment"># 必须在 ['to_hourly', 'to_daily'] 里二选一</span>
  <span class="token key atrule">filter_V</span><span class="token punctuation">:</span>
    <span class="token punctuation">-</span> string
</code></pre><ul>
<li>filter_T: 含时处理，挂载需要时间信息的预处理操作
<ul>
<li>ticker_timer: 时间补全并对齐到时间单位 (h)</li>
<li>ltrim_vacant: 抛弃连续一周以上的缺值及之前</li>
</ul>
</li>
<li>project: 时间刻度投影，并分离时间维度
<ul>
<li>to_hourly: 时间单位固定为小时</li>
<li>to_daily: 时间单位固定为日
<ul>
<li>聚合策略: 当日有效数据 &gt;12h 则取均值，否则置为 NaN</li>
</ul>
</li>
</ul>
</li>
<li>filter_V: 不含时处理，挂载不需要时间信息的预处理操作
<ul>
<li>remove_outlier: 区间端点线性插值以重定 3σ 界外值</li>
<li>wavlet_transform: 小波变换去噪</li>
</ul>
</li>
</ul>
<h5 id="dataset-数据集切片">dataset 数据集切片 </h5>
<pre data-role="codeBlock" data-info="yaml" class="language-yaml yaml"><code><span class="token key atrule">dataset</span><span class="token punctuation">:</span>
  <span class="token key atrule">exclusive</span><span class="token punctuation">:</span> bool   <span class="token comment"># 多特征变量建模是否除外自身 (default: False, ie. auto-gressive)</span>
  <span class="token key atrule">inlen</span><span class="token punctuation">:</span> int        <span class="token comment"># 条件序列窗长，知 in 推 out (default: 3)</span>
  <span class="token key atrule">outlen</span><span class="token punctuation">:</span> int       <span class="token comment"># 预测序列窗长，知 in 推 out (default: 1)</span>
  <span class="token key atrule">overlap</span><span class="token punctuation">:</span> int      <span class="token comment"># in/out 窗重叠长度 (default: 0)</span>
  <span class="token key atrule">split</span><span class="token punctuation">:</span> float      <span class="token comment"># 数据集划分，测试集占比 (default: 0.2)</span>
  <span class="token key atrule">encoder</span><span class="token punctuation">:</span>          <span class="token comment"># 分类任务的目标编码 (default: None)</span>
    <span class="token key atrule">name</span><span class="token punctuation">:</span> string    <span class="token comment"># 编码函数，可选项为 modules/dataset.py 文件内各函数名</span>
    <span class="token key atrule">params</span><span class="token punctuation">:</span>         <span class="token comment"># 编码函数的额外参数列表</span>
      <span class="token punctuation">[</span><span class="token key atrule">key</span><span class="token punctuation">:</span> value<span class="token punctuation">]</span>
  <span class="token key atrule">freq_min</span><span class="token punctuation">:</span> float   <span class="token comment"># 分类任务的非0类占比阈值，小于此阈值将忽略建模 (default: 0.0)</span>
</code></pre><ul>
<li>对 预处理数据data，分离 特征变量序列seq 和 目标变量序列tgt</li>
<li>对于分类任务，对 tgt 打标签得到 lbl；检查异常值是否超出最小建模阈值</li>
<li>知 in 推 out，在 seq 上滚动切片作为 X，对应的 tgt/lbl 作为 Y</li>
<li>对数据集 (X, Y) 做训练-测试划分</li>
</ul>
<pre data-role="codeBlock" data-info="python" class="language-python python"><code><span class="token comment"># data: [T, D'], float      # 预处理后的csv数据表</span>
seq <span class="token operator">=</span> data<span class="token punctuation">[</span><span class="token punctuation">:</span><span class="token punctuation">,</span> <span class="token punctuation">:</span><span class="token operator">-</span><span class="token number">1</span><span class="token punctuation">]</span> <span class="token keyword keyword-if">if</span> exclusive <span class="token keyword keyword-else">else</span> data
tgt <span class="token operator">=</span> data<span class="token punctuation">[</span><span class="token punctuation">:</span><span class="token punctuation">,</span> <span class="token operator">-</span><span class="token number">1</span><span class="token punctuation">]</span>

<span class="token comment"># seq: [T, D], float        # T 个采样点, D 维特征输入</span>
<span class="token comment"># tgt: [T, 1], float        # T 个采样点, 1 维目标输出</span>
<span class="token keyword keyword-if">if</span> task_type <span class="token operator">==</span> <span class="token string">'clf'</span><span class="token punctuation">:</span>
  lbl <span class="token operator">=</span> encode<span class="token punctuation">(</span>tgt<span class="token punctuation">,</span> encoder<span class="token punctuation">)</span>   <span class="token comment"># [N, 1], int</span>
  freq <span class="token operator">=</span> Counter<span class="token punctuation">(</span>lbl<span class="token punctuation">)</span>
  <span class="token keyword keyword-if">if</span> freq <span class="token operator">&lt;</span> freq_min<span class="token punctuation">:</span>       <span class="token comment"># 若异常值太少，则放弃建模 </span>
    <span class="token keyword keyword-return">return</span>

<span class="token comment"># X: [N, I, D], float       # N 帧, 帧长 I，维数 D</span>
<span class="token comment"># Y: [N, O, 1], float/int   # N 帧, 帧长 O，维数 1</span>
X<span class="token punctuation">,</span> Y <span class="token operator">=</span> slice_frames<span class="token punctuation">(</span>seq<span class="token punctuation">,</span> tgt<span class="token operator">/</span>lbl<span class="token punctuation">,</span> inlen<span class="token punctuation">,</span> outlen<span class="token punctuation">,</span> overlap<span class="token punctuation">)</span>

<span class="token comment"># trainset: (X_train, Y_train)</span>
<span class="token comment"># testset: (X_test, Y_test)</span>
trainset<span class="token punctuation">,</span> testset <span class="token operator">=</span> split_dataset<span class="token punctuation">(</span>X<span class="token punctuation">,</span> Y<span class="token punctuation">,</span> split<span class="token punctuation">)</span>
</code></pre><h5 id="transform-数值转换">transform 数值转换 </h5>
<pre data-role="codeBlock" data-info="yaml" class="language-yaml yaml"><code><span class="token key atrule">transform</span><span class="token punctuation">:</span>          <span class="token comment"># 数值变换，可选项为 modules/transform.py 文件内各函数名</span>
  <span class="token punctuation">-</span> string
</code></pre><ul>
<li>数值转换仅面向模型的输入输出界面，必须是可逆计算
<ul>
<li>log: 对数化</li>
<li>std_norm: 均值方差归一化</li>
<li>minmax_norm: 最大最小值归一化</li>
</ul>
</li>
</ul>
<h3 id="模型训练-推断流程">模型训练-推断流程 </h3>
<pre data-role="codeBlock" data-info="yaml" class="language-yaml yaml"><code><span class="token key atrule">model</span><span class="token punctuation">:</span>
  <span class="token key atrule">name</span><span class="token punctuation">:</span> string      <span class="token comment"># 模型模板，可选项为 modules/models 目录下各文件名</span>
  <span class="token key atrule">params</span><span class="token punctuation">:</span>           <span class="token comment"># 依模型模板不同设置项也不同，详见各模板</span>
    <span class="token punctuation">[</span><span class="token key atrule">key</span><span class="token punctuation">:</span> value<span class="token punctuation">]</span>
</code></pre><p>⚠ Just read the fucking code!! ⚠</p>
<hr>
<p>by Armit<br>
2023年2月19日</p>

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